Abstract

This communication aims to present m-RESIST, the first mHealth program for patients with treatment resistant schizophrenia (TRS). The main objective of this European project is to develop an intervention programme to allow TRS patients to self-manage their condition, which is associated with persistent positive symptomatology, extensive periods of hospital care, and a greater risk of excess mortality and multi-morbidity.m-RESIST could offer a new tool for mental health professionals to better monitor TRS patients, providing a tailored and optimized therapeutic intervention. In this sense, m-RESIST will develop and validate a mHealth tool aimed to reduce the severity of episodes and further complications. Moreover, this tool will involve and promote a proactive role of patients and caregivers in the therapeutic process, promoting an active and collaborative role with the medical team in the treatment decision-making procedure.m-RESIST intervention, will integrate: (1) a sensor data analysis module, which will process data coming from smart phone and wearable devices, providing passive information such as movement or social activity; (2) a predictive modeling engine, which will enable prediction of clinically significant events, such as hospitalization, risk behaviors and social isolation; and (3) a clinical decision support system (CDSS), which will provide the users with necessary information to support health-related and clinical decision-making.The pilots of this project will take place in Tel-Aviv, Budapest and Barcelona during May, June and July of 2017. Although cost-effectiveness variables will also be measured, the main assessment will be focused on acceptability, usability, satisfaction, empowerment and quality of life outcomes.Disclosure of interestThe author has not supplied his declaration of competing interest.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.